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Microsoft GH-200 Exam Overview:

Certification Vendor:	Microsoft / GitHub
Exam Name:	GitHub Actions Exam
Exam Number:	GH-200
Related Certifications:	GitHub Advanced Security GitHub Foundations GitHub Copilot
Available Languages:	English
Exam Duration:	120 minutes
Exam Format:	Multiple choice, Multiple response, Scenario-based questions
Recommended Training:	Microsoft Learn: GitHub Actions learning paths GitHub Skills - Actions courses
Exam Registration:	GH-200 Study Guide Microsoft Learn Certification Page
Sample Questions:	Microsoft GH-200 Sample Questions
Exam Way:	Online proctored (Pearson VUE / Microsoft Learn credentialing system)
Pre Condition:	Recommended: intermediate experience with GitHub, CI/CD, and GitHub Actions workflows; familiarity with YAML and DevOps concepts
Official Syllabus URL:	https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/gh-200

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Microsoft GH-200 Prüfungsplan:

Thema	Einzelheiten
Thema 1	Author and Maintain Actions: This domain evaluates the abilities of Action Developers and Automation Engineers to select and create suitable types of GitHub Actions, such as JavaScript, Docker containers, or run steps. It emphasizes troubleshooting action code, understanding the components and file structures of actions, and using workflow commands within actions to communicate with runners, including exit code management.
Thema 2	Manage GitHub Actions in the Enterprise: This section measures the expertise of Enterprise Administrators and Platform Engineers in distributing and managing GitHub Actions and workflows at the organizational level. It includes reuse and sharing of templates, strategies for managing reusable components via repositories and naming conventions, controlling access to actions, setting organization-wide usage policies, and planning maintenance to ensure efficient enterprise-wide deployment of GitHub Actions.
Thema 3	Consume Workflows: This domain targets Software Developers and Quality Assurance Engineers and focuses on interpreting workflow runs and their outcomes. It covers identifying triggering events, reading workflow configurations, troubleshooting failures by analyzing logs, enabling debug logging, managing environment variables, caching dependencies, and passing data between jobs. Candidates also manage workflow runs, artifacts, approvals, and status badges, as well as locating workflows within repositories and leveraging organizational templated workflows.
Thema 4	Author and Maintain Workflows: This section of the exam measures skills of DevOps Engineers and Automation Specialists and covers building and managing workflows triggered by events such as pushes, scheduled times, manual triggers, and webhooks. It includes understanding workflow components like jobs, steps, actions, and runners, syntax correctness, environment variables, secrets management, and dependencies between jobs. Candidates will also demonstrate practical abilities to create workflows for various purposes, including publishing packages, using service containers, routing jobs, and deploying releases to cloud providers.

Microsoft GitHub Actions GH-200 Prüfungsfragen mit Lösungen (Q68-Q73):

68. Frage
How can a workflow deployment mitigate the risk of multiple workflow runs deploying to a single cloud environment simultaneously?
(Each correct answer presents part of the solution. Choose two.)

A. Specify a target environment in the deployment job.
B. Specify a concurrency scope in the workflow.
C. Configure the mutex setting in the environment.
D. Pass the mutex into the deployment job.
E. Reference the mutex in the task performing the deployment.
F. Set the concurrency in the deployment job to 1.

Antwort: A,B

Begründung:
GitHub Actions provides the concurrency mechanism for preventing overlapping workflow runs or jobs that share the same concurrency group. A workflow can define a concurrency group associated with a deployment target so that only one matching deployment is running at a time. The deployment job should also reference the target GitHub environment, such as production, so GitHub can associate the job with that deployment environment and apply its deployment controls. GitHub ' s documentation specifically describes using concurrency to ensure that an environment has a maximum of one deployment in progress at a time. GitHub does not provide the mutex configuration described in options A, B, and F, and concurrency is not configured simply by assigning the numeric value 1. Therefore, specifying the concurrency scope together with the target environment is the appropriate solution.

69. Frage
As a developer, you are using a Docker container action in your workflow. What is required for the action to run successfully?

A. The job env must be set to a Linux environment.
B. The action must be published to the GitHub Marketplace.
C. The referenced action must be hosted on Docker Hub.
D. The job runs-on must specify a Linux machine with Docker installed.

Antwort: D

Begründung:
For a Docker container action to run in a GitHub Actions workflow, the runner must have Docker installed.
The runs-on attribute of the job should specify an environment that supports Docker, typically a Linux environment (e.g., ubuntu-latest), since Docker is widely supported and commonly used in Linux-based environments.

70. Frage
In GitHub Actions, how is the success or failure of a step determined by its exit code?

A. Every exit code is a failure
B. Success is controlled by continue-on-error rather than the exit code
C. Exit codes are ignored and a maintainer sets the result manually
D. Zero exit code means success and any nonzero means failure

Antwort: D

Begründung:
GitHub Actions evaluates each step by the exit status of the process it runs. The runner marks a step successful when the command finishes with an exit status of 0. If the command returns any other code then the step is marked as failed and the job may stop depending on your workflow configuration.

71. Frage
As a DevOps engineer, you are developing a composite action. You have a step that needs to be executed against a subdirectory. Which code snippet should you use within the composite action to specify the directory?

A. runs:
using: " composite "
steps:
- run: $GITHUB_ACTION_PATH/script.sh
working-directory: ${{ inputs.dir }}
shell: bash
B. runs:
using: " composite "
directory: ${{ inputs.dir }}
steps:
- run: $GITHUB_ACTION_PATH/script.sh
shell: bash
C. runs:
using: " composite "
steps:
- run: $GITHUB_ACTION_PATH/script.sh
directory: ${{ inputs.dir }}
shell: bash
D. runs:
using: " composite "
working-directory: ${{ inputs.dir }}
steps:
- run: $GITHUB_ACTION_PATH/script.sh
shell: bash

Antwort: A

Begründung:
For a composite action, commands are defined inside the runs.steps section of the action metadata file. When a specific command must execute from a particular folder, the correct key is working-directory, and it must be applied at the individual run step level. Option D is correct because it keeps using: " composite " at the runs level and applies working-directory: ${{ inputs.dir }} directly to the step that runs the script. Option A is incorrect because directory is not a valid GitHub Actions run-step key. Option B incorrectly places directory at the runs level. Option C uses the right keyword but places it at the wrong level. This tests composite action metadata syntax and correct step-level execution configuration.

72. Frage
What are the two ways to pass data between jobs? (Choose two.)

A. Use the copy action to save the data that should be passed in the artifacts folder.
B. Use data storage.
C. Use job outputs
D. Use the copy action with cache parameter to cache the data
E. Use artifact storage.
F. Use the copy action with restore parameter to restore the data from the cache

Antwort: C,E

Begründung:
Job outputs are used to pass data from one job to another in a workflow. A job can produce output values (like variables or files), which can be referenced by subsequent jobs using the needs keyword and ${{ steps.step_id.outputs.output_name }} syntax.
Artifact storage allows data (such as files or results) to be saved by a job and then retrieved by another job in a later step. This is commonly used for passing large amounts of data or files between jobs.

73. Frage
......

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